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PubMed1975

Confidence intervals for the conditional probability of misallocation in discriminant analysis.

In this study we are concerned with the construction of confidence intervals for the conditional probability of misallocation associated with Anderson's classification statistics, W. The available methods of computing confidence intervals for the conditional probability are not satisfactory in practice, mainly because the intervals obtained are fairly inaccurate. A new method is presented which enables intervals with almost the desired level of confidence to be easily computed from the initial samples on which W is based.

Monte Carlo Method↗
PubMed2006

[Applying patial least-squares discriminant analysis on autofluorescence spectra to identify gastric cancer].

Measurement of fluorescence intensity was performed at excitation wavelength of 308 nm and emission wavelength in the range of 328-596 nm. The partial least-squares (PLS) method was used to analyze autofluorescence spectra of gastric cancer. The 42 normal samples and 42 cancer samples were taken from 42 gastric cancer patients. The normalized and centralized spectra of two kinds of samples showed similar but divergent patterns. PLS classification algorithm could differentiate cancer tissues from normal tissues with a sensitivity of 83.3%, a specificity of 95.2%, and a positive predictive value of 94.6%. We concluded therefore that the PLS method was a fast, effective choice for identification of gastric cancer.

Adult↗